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# Copyright 2022 Huawei Technologies Co., Ltd
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# ==========================================================================

# -*- coding: utf-8 -*-
# BSD 3-Clause License
#
# Copyright (c) 2017
# All rights reserved.
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
#   list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
#   this list of conditions and the following disclaimer in the documentation
#   and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its
#   contributors may be used to endorse or promote products derived from
#   this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# ==========================================================================

// Copyright (c) OpenMMLab. All rights reserved
#include "pytorch_cpp_helper.hpp"
#include "pytorch_device_registry.hpp"

void carafe_forward_impl(Tensor features, Tensor masks, Tensor rfeatures,
                         Tensor routput, Tensor rmasks, Tensor output,
                         int kernel_size, int group_size, int scale_factor) {
  DISPATCH_DEVICE_IMPL(carafe_forward_impl, features, masks, rfeatures, routput,
                       rmasks, output, kernel_size, group_size, scale_factor);
}

void carafe_backward_impl(Tensor top_grad, Tensor rfeatures, Tensor masks,
                          Tensor rtop_grad, Tensor rbottom_grad_hs,
                          Tensor rbottom_grad, Tensor rmask_grad,
                          Tensor bottom_grad, Tensor mask_grad, int kernel_size,
                          int group_size, int scale_factor) {
  DISPATCH_DEVICE_IMPL(carafe_backward_impl, top_grad, rfeatures, masks,
                       rtop_grad, rbottom_grad_hs, rbottom_grad, rmask_grad,
                       bottom_grad, mask_grad, kernel_size, group_size,
                       scale_factor);
}

void carafe_forward(Tensor features, Tensor masks, Tensor rfeatures,
                    Tensor routput, Tensor rmasks, Tensor output,
                    int kernel_size, int group_size, int scale_factor) {
  carafe_forward_impl(features, masks, rfeatures, routput, rmasks, output,
                      kernel_size, group_size, scale_factor);
}

void carafe_backward(Tensor top_grad, Tensor rfeatures, Tensor masks,
                     Tensor rtop_grad, Tensor rbottom_grad_hs,
                     Tensor rbottom_grad, Tensor rmask_grad, Tensor bottom_grad,
                     Tensor mask_grad, int kernel_size, int group_size,
                     int scale_factor) {
  carafe_backward_impl(top_grad, rfeatures, masks, rtop_grad, rbottom_grad_hs,
                       rbottom_grad, rmask_grad, bottom_grad, mask_grad,
                       kernel_size, group_size, scale_factor);
}
